scholarly journals Efficient sampling of thermal averages of interacting quantum particle systems with random batches

2021 ◽  
Vol 154 (20) ◽  
pp. 204106
Author(s):  
Xuda Ye ◽  
Zhennan Zhou
Keyword(s):  
Quantum Particle ◽  
Particle Systems ◽  
Efficient Sampling

scholarly journals HIDDEN SCALE IN QUANTUM MECHANICS

2009 ◽  
Vol 24 (27) ◽  
pp. 2203-2211 ◽  
Author(s):  
PULAK RANJAN GIRI
Keyword(s):  
Wave Packet ◽  
Quantum Particle ◽  
Dimensional Space ◽  
Free Particle ◽  
Three Dimensional ◽  
Particle Systems ◽  
Quantum Mechanical ◽  
Scale Invariant ◽  
Mechanical Models ◽  
Three Dimensional Space

We show that the intriguing localization of a free particle wave-packet is possible due to a hidden scale present in the system. Self-adjoint extensions (SAE) is responsible for introducing this scale in quantum mechanical models through the nontrivial boundary conditions. We discuss a couple of classically scale invariant free particle systems to illustrate the issue. In this context it has been shown that a free quantum particle moving on a full line may have localized wave-packet around the origin. As a generalization, it has also been shown that particles moving on a portion of a plane or on a portion of a three-dimensional space can have unusual localized wave-packet.

scholarly journals Exactly solvable quantum few-body systems associated with the symmetries of the three-dimensional and four-dimensional icosahedra

2016 ◽  
Vol 1 (1) ◽  
Author(s):  
Thibault Scoquart ◽  
Joseph Seaward ◽  
Steven Glenn Jackson ◽  
Maxim Olshanii
Keyword(s):  
Quantum Particle ◽  
Three Dimensional ◽  
Particle Systems ◽  
Parametric Family ◽  
Half Line ◽  
Reflection Groups ◽  
Exactly Solvable ◽  
Solvable Quantum ◽  
Regular Icosahedron

The purpose of this article is to demonstrate that non-crystallographic reflection groups can be used to build new solvable quantum particle systems. We explicitly construct a one-parametric family of solvable four-body systems on a line, related to the symmetry of a regular icosahedron: in two distinct limiting cases the system is constrained to a half-line. We repeat the program for a 600600-cell, a four-dimensional generalization of the regular three-dimensional icosahedron.

Statistical 3D Analysis and Modeling of Complex Particle Systems based on Tomographic Image Data

2019 ◽  
Vol 56 (12) ◽  
pp. 787-796
Author(s):  
O. Furat ◽  
B. Prifling ◽  
D. Westhoff ◽  
M. Weber ◽  
V. Schmidt
Keyword(s):  
Image Data ◽  
Particle Systems ◽  
3D Analysis ◽  
Tomographic Image ◽  
Complex Particle

Fault Diagnosis of Wind Turbine Gearbox Based on Improved QPSO Algorithm

2019 ◽  
Vol 12 (3) ◽  
pp. 277-283
Author(s):  
Jiatang Cheng ◽  
Yan Xiong
Keyword(s):  
Particle Swarm Optimization ◽  
Fault Diagnosis ◽  
Wind Turbine ◽  
Bp Neural Network ◽  
Quantum Particle ◽  
Particle Swarm ◽  
Wind Turbine Gearbox ◽  
Bp Network ◽  
Swarm Optimization ◽  
Quantum Particle Swarm Optimization

Background: The effective diagnosis of wind turbine gearbox fault is an important means to ensure the normal and stable operation and avoid unexpected accidents. Methods: To accurately identify the fault modes of the wind turbine gearbox, an intelligent diagnosis technology based on BP neural network trained by the Improved Quantum Particle Swarm Optimization Algorithm (IQPSOBP) is proposed. In IQPSO approach, the random adjustment scheme of contractionexpansion coefficient and the restarting strategy are employed, and the performance evaluation is executed on a set of benchmark test functions. Subsequently, the fault diagnosis model of the wind turbine gearbox is built by using IQPSO algorithm and BP neural network. Results: According to the evaluation results, IQPSO is superior to PSO and QPSO algorithms. Also, compared with BP network, BP network trained by Particle Swarm Optimization (PSOBP) and BP network trained by Quantum Particle Swarm Optimization (QPSOBP), IQPSOBP has the highest diagnostic accuracy. Conclusion: The presented method provides a new reference for the fault diagnosis of wind turbine gearbox.

Sign in / Sign up

Export Citation Format

Share Document